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It is widely acknowledged that the value of a house is the mixture of a large number of characteristics. House price prediction thus presents a unique set of challenges in practice. While a large body of works are dedicated to this task, their performance and applications have been limited by the shortage of long time span of transaction data, the absence of real-world settings and the insufficiency...
Matrix Factorization (MF) is a very popular method for recommendation systems. It assumes that the underneath rating matrix is low-rank. However, this assumption can be too restrictive to capture complex relationships and interactions among users and items. Recently, Local LOw-Rank Matrix Approximation (LLORMA) has been shown to be very successful in addressing this issue. It just assumes the rating...
This paper presents a methodology for optimizing the size of energy storage system (ESS) for maximizing the capture of energy regenerated by a train. Besides, minimization of energy consumption from the substation, in order to obtain a return on investment, has also been explored. A standard structure of rail transit system has been used here for analysis. The optimization process takes into account...
We consider tracking of a target with elliptical nonlinear constraints on its motion dynamics. The state estimates are generated by sensors and sent over long-haul links to a remote fusion center for fusion. We show that the constraints can be projected onto the known ellipse and hence incorporated into the estimation and fusion process. In particular, two methods based on (i) direct connection to...
This paper shows the relationship between switching/sampling frequency, samples number and sine wave fundamental frequency with the intention of giving a basis to understand how the algorithm was designed. It also punctuates mathematical and implementation constraints considered in the optimization algorithm design. Similarly it explains the numerical methods and procedures used in the algorithm to...
The increase in the size of the data used in natural language processing activities brings with it time and space constraints. Thus, it is important to both store and access data efficiently. This study includes experiments for storing the term-document index, which will be used in a natural language processing project, effectively in memory. For this purpose, the indexed data is compressed using...
Recently, fault indicators with communication function have been increasingly used in fault diagnosis of distribution networks. In this paper, an objective function which considers the reliability index of the distribution network and economic factors synthetically has been proposed for optimal placement of fault indicators in distribution networks, and binary particle swarm optimization algorithm...
In ultra-dense cellular networks, research works on enhancing cell edge performance receive considerable attention. Based on interlaced clustering, we propose a heuristic sparse beamforming strategy to improve the cell edge throughput effectively in distributed antenna systems (DASs). In our scheme, each cluster pattern (CP) is divided into several adaptive cells, where all the remote antenna units...
Distributed generation (DG) is utilized in electric power networks for the purpose of loss reduction, environment friendly features, and voltage improvement. This paper determines optimal allocation of DGs through Multi-Objective Index (MOI) for improving voltage stability and decreasing line losses of radial distribution system. Multiple objectives are merged using weighting factors and investigated...
Owing to its simplicity and efficacy, orthogonal matching pursuit (OMP) has been a popular sparse representation method for compressed sensing and pattern classification. As a recent extension of OMP, generalized OMP (GOMP) improves the efficiency of OMP by identifying multiple atoms each iteration. Nonetheless, GOMP utilizes the mean square error (MSE) criterion as the loss function, which has been...
Closing gate valves at the boundaries of District Metering Areas (DMAs) in Water Distribution Networks (WDNs) allows reducing pressure and leakages through the WDN, as a consequence of changing the hydraulic paths of the system. A two-step strategy was recently proposed for accomplishing such a task. The first step is the optimal segmentation design, based on maximizing the WDN-oriented modularity...
This paper introduces compact music-inspired computing. We propose a music-inspired optimization technique with minimal computational cost. The aim is to reduce the memory storage capacity required by the classical harmony search algorithm (HSA) while improving their performance. Therefore, we propose three compact harmony search algorithms. The main idea is to represent the harmonies stored in the...
The decode-and-forward (DF) relay based cellular network is considered an efficient technique for solving the coverage and improving system capacity of the current fourth-generation (4G) and the emerging fifth-generation (5G) mobile telecommunication technologies. In this analysis, we control the codeword's transmission parameters by achieving a good trade-off between setting more resources with changing...
We propose a new algorithm for portfolio optimization based on statistical arbitrage, that uses a multi-criteria decision making approach to obtain the most preferred assets. A preference flow graph of financial assets is constructed at each time step, with the aid of statistical arbitrage algorithm that describes preferences among the assets. Then, the individual preferences for each asset are obtained...
Under the framework of South American Council of Infrastructure and Planning (Cosiplan — IIRSA in Spanish) project, related on the management of hazard and risk on regional infrastructure (South America), it is presented a new methodology for the identification of vulnerabilities on the infrastructure and their hazards. The Chilean methodology Management of Risk Disasters at Local level (GRDR in Spanish)...
This article covers the comparison of a primitive Dissipating-Predictive-State Planning Actor-Critic learning approach with SARSA(λ) (State-Action-Reward-State-Action) on the highly non-stationary competitive Cat and Mouse problem. The primary objective of the new algorithm was to minimize the number of constants that must be optimized before application while maintaining the performance found in...
This paper introduces a new initialization method of individuals for genetic algorithm (GA) in portfolio optimization problems. In our approach, first a set of assets, variables, composing the portfolio is selected, and then combination of real-valued weights of the portfolio is optimized by GA. In the asset selection, a pairwise asset selection which is an iterative greedy scheme based on the bordered...
Modularity is an evaluation measure for graph clustering. Louvain method is constructed by local optimization for modularity and is bottom up method as well as agglomerative hierarchical clustering. Cluster validity measures are used to evaluate cluster partitions as well as modularity. They are traditional evaluation measures in the field of clustering. We propose a novel graph clustering which is...
Nowadays, Rate-Distortion Optimization (RDO) is commonly used in hybrid video coding to maximize coding efficiency. Usually, the rate distortion tradeoff is explicitly computed in offline encoder implementations whereas R(D) model are used in live encoders to select the best decisions at a lower computational cost. For sake of simplicity, this (mathematical) modelling is often performed for each coding...
In this paper a Markov decision process (MDP) model for virtualized content delivery networks is proposed. We use stochastic optimization to assign cloud site resources to each user group. We propose how quality of experience (QoE) can be included in the modeling and optimization. We then present an optimal solution for a constraint-free version of the problem, and show the improvement in accumulated...
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